BI integration
Discussion of efforts to integrate text analytics with business intelligence and other analytic technologies. Related subjects include:
The phrase “business intelligence” was COINED for text analytics
Late last year, there was a little flap about who invented the phrase business intelligence. Credit turns out to go to an IBM researcher named H. P. Luhn, as per this 1958 paper. Well, I finally took a look at the paper, after Jeff Jones of IBM sent over another copy. And guess what? It’s all about text analytics. Specifically, it’s about what we might now call a combination of classification and knowledge management.
Half a century later, the industry is finally poised to deliver on that vision.
| Categories: BI integration, Categorization and filtering, IBM and UIMA | 2 Comments |
6 trends that could shake up the text analytics market
My last two posts were based on the introductory slide to my talk The Text Analytics Marketplace: Competitive landscape and trends. I’ll now jump straight ahead to the talk’s conclusion.
Text analytics vendors participate in the same trends as other software and technology vendors. For example, relational business intelligence and data warehousing products are increasingly being sold to departmental buyers. Those buyers place particularly high value on ease of installation. And golly gee whiz, both parts of that are also true in text mining.
But beyond such general trends, I’ve identified six developments that I think could radically transform the text analytics market landscape. Indeed, they could invalidate the neat little eight-bucket categorization I laid out in the prior post. Each is highly likely to occur, although in some cases the timing remains greatly in doubt.
These six market-transforming trends are:
- Web/enterprise/messaging integration
- BI integration
- Universal message retention
- Portable personal profiles
- Electronic health records
- Voice command & control
| Categories: BI integration, Enterprise search, Google, Microsoft, Search engines, Social software and online media, Text mining | 1 Comment |
The Text Analytics Marketplace: Competitive landscape and trends
As I see it, there are eight distinct market areas that each depend heavily on linguistic technology. Five are off-shoots of what used to be called “information retrieval”:
1. Web search
2. Public-facing site search
3. Enterprise search and knowledge management
4. Custom publishing
5. Text mining and extraction
Three are more standalone:
6. Spam filtering
7. Voice recognition
8. Machine translation
Attivio tries to do it all
When Andrew McKay was at FAST, I grumped about his search/BI integration story. Now that he’s trying to do the same thing at a startup called Attivio, it sounds more plausible.
Attivio is having a house party and product rollout in the latter part of January, and details are scarce in the mean time. But here are some highlights.
- Attivio was founded in August. It has 21 people and 1 VC. The VC has invested >$6 million and committed >$12 million total.
- Attivio has ambitious plans for a fully integrated data management/real-time BI stack. It’s currently called the “Active Intelligence Engine.”
| Categories: Attivio, BI integration, Investment research and trading, Lucene, Open source text analytics | 2 Comments |
Clarabridge does SaaS, sees Inxight
I just had a quick chat with text mining vendor Clarabridge’s CEO Sid Banerjee. Naturally, I asked the standard “So who are you seeing in the marketplace the most?” question. Attensity is unsurprisingly #1. What’s new, however, is that Inxight – heretofore not a text mining presence vs. commercially-focused Clarabridge – has begun to show up a bit this quarter, via the Business Objects sales force. Sid was of course dismissive of their current level of technological readiness and integration – but at least BOBJ/Inxight is showing up now.
The most interesting point was text mining SaaS (Software as a Service). When Clarabridge first put out its “We offer SaaS now!” announcement, I yawned. But Sid tells me that about half of Clarabridge’s deals now are actually SaaS. The way the SaaS technology works is pretty simple. The customer gathers together text into a staging database – typically daily or weekly – and it gets sucked into a Clarabridge-managed Clarabridge installation in some high-end SaaS data center. If there’s a desire to join the results of the text analysis with some tabular data from the client’s data warehouse, the needed columns get sent over as well. And then Clarabridge does its thing.
| Categories: BI integration, Clarabridge, Comprehensive or exhaustive extraction, IBM and UIMA, Software as a Service (SaaS), Text mining, Text mining SaaS | 1 Comment |
Everybody’s talking about structured/unstructured integration
Today’s big news is IBM’s $5 billion acquisition of Cognos. Part of the analyst conference call was two customer examples of how the companies had worked together in the past — and one of those two had a lot of “integration of structured and unstructured data.” The application sounded more like a 360-degree customer view, retrieving text documents alongside relational records, than it did like hardcore text analytics. Even so, it illustrates a trend that I was seeing even before BOBJ’s buy of Inxight, namely an increasing focus in the business intelligence world on at least the trappings of text analytics.
| Categories: BI integration, Business Objects and Inxight, IBM and UIMA | 3 Comments |
Business Objects-Inxight update
I’m at the Business Objects annual user conference, and had a couple of chances to talk with Inxight/text analytics folks. When I asked about areas of commercial application traction, answers were similar to those I got from Attensity and Clarabridge, but not quite the same. Specifically:
- Voice of the Customer is definitely tops.
- Some of the other applications Attensity and Clarabridge mentioned appear as well (e.g., antifraud).
- Business Objects also has a couple of customers looking at text mining as an aid to medical records, e.g. by helping to catch errors in tabular-field coding.
- There are some projects in actual investment research/analysis/trading, e.g. in correlating news announcements and stock price movements.
The Business Objects/Inxight folks also made a couple of interesting general technical points.
| Categories: Application areas, BI integration, Business Objects and Inxight, Investment research and trading, Voice of the Customer | Leave a Comment |
SAP is acquiring Inxight
More precisely, SAP is acquiring Business Objects, and of course Business Objects already acquired Inxight.
This could be interesting …
| Categories: BI integration, Business Objects and Inxight, SAP, Text mining | Leave a Comment |
The Clarabridge approach to text mining
And for my sixth text mining post this weekend, here are some highlights of the Clarabridge technology story. (Sorry if it sounds clipped, but I’m a bit burned out …)
- Like Attensity, Clarabridge practices exhaustive extraction.* That is, they do linguistics against documents, extract all sorts of entities and relationships among the entities from each document, and dump the results into a relational database.
- Unlike Attensity, which uses a simple normalized relational schema, Clarabridge dumps the extracted data into a star schema. (The Clarabridge folks are from Microstrategy, which – surely not coincidentally – also favors star schemas.)
| Categories: BI integration, Clarabridge, Comprehensive or exhaustive extraction, Ontologies, Text mining | 2 Comments |
The case for Inxight Awareness Server
I’ve been pretty skeptical about Inxight’s Awareness Server. My theory is that ordinary enterprise search engines can index remotely anyway, and they offer much better search functionality. Inxight’s Ian Hersey was kind enough to write in and offer two counter-arguments.
First, Ian points out that there are circumstances when, due to security and permissions, you can’t really index everything via one search engine. Specifically, he offers the government as an example. OK, I can see that in the government, with its classified and/or regulated silos. However, I have trouble thinking of many more examples. While there certainly are plenty of instances where a variety of organizations share information on a somewhat arms-length basis, it’s tough to think of such cases where federated text search would come into play.
Second, Ian in essence disputes my claim of inferior functionality. While implicitly conceding — as well he should! — that Inxight’s Awareness Server doesn’t do some things full-featured search engines do, he points out analytic features that may not be found in conventional search engine offering. The big one he calls out is faceted search — which of course was the core of Intelliseek,the acquisition Awareness Server came from. Hmm. Faceted search has a checkered history, with Excite and Northern Light being perhaps the most visible among many failures. On the other hand, it’s a great idea that keeps being tried, and some versions — notably Endeca’s — have turned out well.
I guess I’ll have to reserve judgment on that part until I look at Inxight’s product and see what they do and don’t actually have.
